Should You Remove Incentivized Reviews From Customer Feedback Analysis?

The review that confused everyone

Imagine you're cleaning up your feedback data and you spot it: a review tagged as both a verified purchase and an incentivized review. Two badges. Contradictory, right? One says the person actually bought the product. The other says they were paid to write about it. Which one do you trust?

This is one of the most common points of confusion when teams start working with review data. And the answer, perhaps surprisingly, is both tags can be true at the same time.

A customer can buy something and still be incentivized to review it.

Here's what actually happens. A customer buys a product. A few weeks later, the brand sends them a gift card and asks them to leave a review. They do. That review is now both a verified purchase and an incentivized review. Where it gets complicated is that different teams interpret this differently. Some see it as completely normal. Others feel that any incentive taints the review and want it removed. Neither is objectively right. What matters is what you're trying to learn from the data, and whether these reviews are helping or hurting that goal.

Filtering incentivized reviews is not always the right call

In most feedback platforms, removing incentivized reviews is a simple filter. One click, and they're gone. But before you do that, it helps to ask: how many reviews are we actually talking about?

When Wonderflow analyzed this across more than 40 product categories, the answer was surprising. In the vast majority of categories, fewer than 2% of verified purchase reviews were also tagged as incentivized. At that volume, removing them barely changes your data at all. It's a lot of effort for very little impact.

The categories where the number was higher, sometimes up to 16%, weren't suffering from data problems. The pattern was tied to specific channels and marketing strategies. Once you understand that context, it looks less like noise and more like a characteristic of how that channel operates.

The bigger problem: the platform tag isn't always reliable

Here's something most people don't think about. The incentivized badge on a review comes from the platform where the review was posted. You didn't assign it. You have no control over how accurately it's applied.

Some reviews get tagged as incentivized even when the reviewer never mentioned any promotion in their text. Others that were clearly written as part of a campaign slip through without any tag at all. The badge is a starting point, not a verdict.

A more reliable approach is to look at the language of the review itself. When someone writes "I received this product as part of a promotion" or "provided for testing purposes," that's a much stronger signal than a badge assigned by an algorithm. Scanning for these phrases gives you a filter you actually control.

When Wonderflow applied this text-based detection alongside the platform tags, they were able to reduce the noise in one category by 89% and eliminate it entirely in another. The reason? Many reviews tagged as incentivized by the platform contained no indication of a promotion in the actual text, meaning the tag was likely a false positive.

So, what should you actually do?

Start by looking at the data before removing anything. Understand how many reviews are affected and whether the pattern makes sense given your channels and product categories. If the number is small, removing them may not be worth it. If it's large, find out why before you act.

If you do want to filter, use text-based detection rather than relying entirely on platform badges. It's more accurate and gives you confidence in what you're keeping.

if a review carries both badges, don't treat it as an error. It's almost certainly not. It's just a customer who bought the product and was later asked to write about it and that still tells you something real.